Name
Abstract | ||
|---|---|---|
Word segmentation is a critical stage towards word and character recognition as well as word spotting and mainly concerns two basic aspects, distance computation and gap classification. In this paper, we propose a robust evaluation methodology that treats the distance computation and the gap classification stages independently. The detection rate calculated for every distance metric corresponds to the maximum detection rate that we could have achieved if we had a perfect classifier for the gap classification stage. The proposed evaluation framework has been applied to several state-of-the-art techniques using a handwritten as well as a historical typewritten document set. The best combination of distance metric computation and gap classification state-of-the-art techniques is proposed. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICDAR.2009.219 | ICDAR-1 |
Keywords | Field | DocType |
distance computation,stage evaluation methodology,word segmentation techniques,detection rate,word segmentation,gap classification stage,maximum detection rate,gap classification,gap classification state-of-the-art technique,distance metric computation,distance metric corresponds,critical stage,distance metric,image segmentation,robustness,art,handwriting recognition,evaluation,computational intelligence,text analysis,informatics,image classification,accuracy,euclidean distance,image analysis | Computer vision,Pattern recognition,Computer science,Euclidean distance,Word error rate,Metric (mathematics),Handwriting recognition,Text segmentation,Image segmentation,Artificial intelligence,Classifier (linguistics),Contextual image classification | Conference |
Citations | PageRank | References |
1 | 0.36 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Georgios Louloudis | 1 | 81 | 9.54 |
| Nikolaos Stamatopoulos | 2 | 38 | 3.06 |
| Basilis Gatos | 3 | 773 | 43.34 |